innovation in performance measurement trends and research implications

JMARVolume Ten

1998

Innovations in PerformanceMeasurement: Trends and Research

ImplicationsChristopher D. Ittner

David F. LarckerUniversity of Pennsylvania

Abstract: The objective of this paper is to foster research on recent innova-tions in performance measurement by providing a rich description of emergingmeasurement practices and suggesting directions for future research. Usingsurvey data coiiected by consuiting firms and government organizations, weexamine three measurement trends: (1) economic vaiue measures, (2) nonfi-nancial performance measures and the balanced scorecard, and (3) perform-ance measurement initiatives in government agencies. Existing research onthese topics is reviewed and research opportunities are highlighted.

The choice of performance measures is one of the most critical chal-lenges facing organizations. Performance measurement systems play a keyrole in developing strategic plans, evaluating the achievement of organi-zational objectives, and compensating managers. Yet many managers feelthat traditional accounting-based measurement systems no longer ade-quately fulfill these functions. A 1996 survey by the Institute of Manage-ment Accounting (IMA) found that only 15 percent of the respondents'measurement systems supported top management's business objectiveswell, while 43 percent were less than adequate or poor. In response, firmsincreasingly are Implementing new performance measurement systems toovercome these limitations. Sixty percent of the IMA respondents, for ex-ample, reported they were undertaking a major overhaul or planning toreplace their performance measurement systems.

The perceived inadequacies in traditional accounting-based perform-ance measures have motivated a variety of performance measurement in-novations ranging from "improved" financial metrics such as "economicvalue" measures to "balanced scorecards" of integrated financial and non-financial measures. However, despite increasing adoption of these per-formance measurement innovations, relatively few studies have examinedthe new measures' economic relevance, the implementation issues arisingfrom their adoption, or the performance consequences from their use. Theobjective of this paper is to foster research on these topics by: (1) providinga rich description of emerging performance measurement practices, (2)synthesizing current research on the use and performance consequencesof the new measures, and (3) suggesting directions for future research.

Financial support was provided by Ernst & Young LLP and KPMG Peat Marwick LLP. Theconvnents o/Madhav RaJan and the research assistance oJTim Meyer are greatly appreciated.We are especially indebted to AT&T, Ernst & Young, Sibson & Co., Towers Perrin, and theUnited States General Accounting Office Jor providing data reported in this paper.

206 Journal of Management Accounting Research, 1998

The remainder of the paper is organized into five sections. The nextsection reviews emerging trends in performance measurement practices.The following sections discuss three topics that have dominated recentperformance measurement discussions: (1) economic value measures, (2)nonfinancial measures and the balanced scorecard, and (3) performancemeasurement initiatives in government agencies. The final section offersour conclusions.

TRENDS IN PERFORMANCE MEASUREMENTMost economic theories analyzing the choice of performance measures

indicate that performance measurement and reward systems should in-corporate any financial or nonfinancial measure that provides incrementalinformation on managerial effort (subject to its cost).^ Despite these mod-els, firms traditionally have relied almost exclusively on financial mea-sures such as budgets, profits, accounting returns and stock returns formeasuring performance (Balkcom et al. 1997). Many firms now believethat the heavy emphasis placed on financial measures is inconsistent withtheir relative importance. Wm. Schiemann and Associates surveyed 203executives in 1996 on the quality, uses and perceived importance ofvarious financial and nonfinancial performance measures (Lingle andSchiemann 1996). Their results are presented in table 1. While 82 percentof the respondents valued financial information highly, more than 90 per-cent clearly defined financial measures in each performance area, in-cluded these measures in regular management reviews, and linked com-pensation to financial performance. In contrast, 85 percent valuedcustomer satisfaction information highly, but only 76 percent includedsatisfaction measures in management reviews, just 48 percent clearly de-fined customer satisfaction for each performance area or used these mea-sures for driving organizational change, and only 37 percent linked com-pensation to customer satisfaction. Similar disparities exist for measuresof operating efficiency, employee performance, community and environ-ment, and innovation and change. More importantly, most executives hadlittle confidence in any of their measures, with only 61 percent willing tobet their jobs on the quality of their financial performance information andonly 41 percent on the quality of operating efficiency indicators, the high-est rated nonfinancial measure.

Perceived inadequacies in traditional performance measurement sys-tems have led many organizations to place greater emphasis not only onnonfinancial measures, but also on "improved" financial measures. Theincreased emphasis on performance measures of all kinds is refiected indata from Ernst & Young's 1991 International Quality Study (IQS 1991)of 584 businesses in four countries (Canada, Germany, Japan and theUnited States) and four industries (automobile, banking, computer andhealth care). Table 2 lists the importance of various financial and nonfi-nancial process improvement, strategic planning, and compensation mea-sures in 1988 and 1991, and their expected importance in 1994. The pro-cess improvement responses indicate that each of the measures, includingreduced costs, increased in importance over time. Whereas reduced cost

' See Holmstrom (1979). Banker and Datar (1989) and Feltham and Xle (1994).

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TABLE 2Changes in Performance Measures Used for Evaluating Process

Improvements, Strategic Planning, and Compensation1991 Ernst & Young Survey of Manufacturing and Service Firms

iu Four Countries*

1994 ANOVA1988 1991 (Expected) F-statistic

Importance of the following measures for evaluating processimprovements:"

Reduced costsReduced errorsReduced cycle timeLess process variationFewer customer

complaints

3.012.772.492.18

2.92

3.313.222.912.74

3.32

3.523.553.323.31

3.64

61.07***144.35***126.74***208.03***

112.11***Importance of the following measures in the strategic-planning process:**

Customer satisfaction 2.59 3.13 3.67 233.21***

Importance of the following assessment criteria for compensation:**

Senior management

QualityStock appreciationProfit or cash flowMarket share or other

positional measure

Middle management

QualityStock appreciationProflt or cash flowMarket share or other

posltionai measure

QualityStock appreciationProflt or cash flowMarket share or other

posltionai measure

2.221.862.91

2.31

2.191.452.48

1.97

2.031.181.84

1.54

2.622.003.15

2.53

2.551.492.68

2.14

2.291.201.96

1.64

3.142.153.27

2.81

3.131.692.93

2.49

2.851.352.27

1.96

137.99***5.91***

19.29***

33.64***

133.16***7.63***

26.73***

37.71***

86.69***6.84***

23.78***

27.82***

*** Responses across years are statistically different at the 1 percent level.''The International Quality Study (IQS) was a joint survey of 584 organizations byErnst & Young and the American Quality Foundation. The survey was conductedIn the automobile, computer, banking and health care industries In Canada, Ger-many, Japan and the United States.

•"Deflnitlon of scales: 1 = slight or not at all (trivial or no concern at all), 2= secondary (less important, but not trivial), 3 = major (Important, together withothers), 4 = primary (dominant).

Ittner arvi Larcker 209

was the most important process measure in 1988, it ranked lower thanthe number of customer complaints in 1991 and was expected to rankbelow customer complaints and reduced errors by 1994. Similarly, theImportance of customer satisfaction measures in strategic planning in-creased significantly from 1988 to 1991, and was expected to increaseeven further by 1994. Compensation assessment criteria exhibit similarpatterns. The use of nonfinancial measures such as customer satisfactionand market share became significantly more important in compensationdecisions at all organizational levels. However, financial measures such asstock appreciation, profits and cash flows also became more important,refiecting an overall increase in pay-for-performance as well as greater useof nonfinancial measures.

Additional analysis of the IQS data (not reported) Indicates that thesetrends are not limited to manufacturing or North American firms. In eachindustry and country, customer satisfaction measures became increas-ingly important for strategic planning, and nonfinancial measures suchas reductions in customer complaints and process variability played agreater role in assessing process improvements. With the exception ofstock appreciation in German businesses, western organizations reportedgreater use of each of the compensation criteria at all organizational levels.Industry-specific tests also found significant increases in the importanceplaced on nearly all of the compensation measures. Japanese firms, how-ever, reported few changes in compensation criteria; the only significantdifference over time (p < 0.10, two-tail) was greater use of quality mea-sures for senior management compensation.

The increased emphasis on both financial and nonfinancial measuresis consistent with two trends that have dominated recent performancemeasurement discussions: (1) the addition of "new" financial measuresthat are claimed to overcome some of the limitations of traditional financialperformance measures, and (2) greater emphasis on "forward-looking"nonfinancial measures such as customer satisfaction, employee satisfac-tion and defect rates. We review these trends in the following sections.

"ECONOMIC VALUE" MEASURESWhile traditional accounting measures such as earnings per share and

return on investment are the most common performance measures, theyhave been criticized for not taking into consideration the cost of capitaland for being unduly infiuenced by external reporting rules. Consultingfirms are promoting a variety of "economic value" measures to overcomethese limitations. The foundations for these "new" performance measuresare residual income and internal rate of return concepts developed in the1950s and 1960s. Stern Stewart & Co.'s (hereafter Stern Stewart) trade-marked "Economic Value Added" or EVA® measure, for example, is thefirm's proprietary adaptation of residual income. EVA® is defined as ad-justed operating income minus a capital charge, and assumes that a man-ager's actions only add economic value when the resulting profits exceedthe cost of capital. To eliminate perceived distortions created by externalaccounting rules. Stern Stewart recommends up to 160 adjustments thatfirms can make to their accounting systems to more closely approximate


"economic" profits. Common adjustments to compute EVA® include mod-ifications to the deferred income t£ix reserve, the LIFO reserve, the treat-ment of intangible assets such as research and development and adver-tising, and goodwill amortization (see Stewart [1991, 113-117], for otherrecommended adjustments).

A second economic value measure that has received considerable at-tention is "Cash Flow Return on Investment" (CFROI) and its variants.CFROI essentially is the long-term internal rate of return, calculated bydividing infiation-adjusted cash fiow by the infiation-adjusted cash in-vestment (Snyder 1995). Advocates of CFROI argue that this metric isvastly superior to traditional accounting measures and EVA® as a per-formance measure. In an article on the "metric wars" between consultingfirms pushing various economic value measures, a partner at HOLT ValueAssociates claimed, "CFROIs are ideally suited to displaying long-termtrack records, whereas a Stern Stewart-tj^ie EVA is in millions of dollars,heavily infiuenced by asset size, and unadjusted for infiation-induced bi-ases" (Myers 1996, 41). Responded Stern Stewart co-founder G. BennetStewart III, "CFROI is literally a consultant's concoction. It was quite animaginative development by a consulting firm, but it is not well groundedin the basic elements of corporate finance theory. CFROI attempts to mea-sure shareholder wealth—which is not clearly related to maximizingshareholder wealth" (Myers 1996, 42).

A number of impressive claims have been made for each of the eco-nomic value measures. Stern Stewart, for example, cites in-house re-search indicating that "EVA® stands well out from the crowd as the singlebest measure of wealth creation on a contemporaneous basis" (Stewart1991, 75), while Dixon and Hedley (1993) of Braxton Associates cite aninternal study showing their CFROI measure explains 91 percent of thevariation in market capitalization ratios. Claims such as these haveprompted a growing number of firms to adopt various forms of economicvalue measures. A 1996 survey by the Institute of Management Account-ants (IMA 1996) found that 35 percent of the respondents used EVA® orsimilar measures (up from 18 percent in 1995) and 45 percent expectedto use them in the future (up from 27 percent in 1995). Yet, despite theincreasing emphasis on these measures, research on the extent to whichthey are superior to traditional accounting measures is limited and mixed.

The Association Between Economic Value Measures and StockReturns

Most studies to date have examined claims that EVA® is a better pre-dictor of stock returns than traditional accounting measures. Milunovichand Tseui's (1996) examination of the computer server industry foundmarket-value added between 1990 and 1995 more highly correlated withEVA® than with earnings per share, earnings per share growth, return onequity, free cash fiow, or free cash growth. Lehn and Makhija (1997) alsofound that stock returns over a ten-year period were more highly corre-lated with average EVA® over the period than with average ROA, ROS, orROE. In addition, EVA® performed somewhat better than accounting prof-its in predicting CEO turnover. O'Byrne (1996) examined the associationbetween market value and two performance measures: EVA® and net op-erating profit after tax (NOPAT). He found that both measures had similar

Ittner and Larcker 211

explanatory power when no control variables were included in the regres-sion models, but that a modified EVA® model had greater explanatorypower when indicator variables for 57 industries and the log of capital foreach firm were included as additional explanatory variables. However,O'Byrne (1996) did not make similar adjustments to the NOPAT model,making it impossible to compare results using the different measures.

Other studies suggest that EVA® is predictive of stock returns, but isnot the only performance measure that ties directly to a stock's intrinsicvalue, one of the primary claims of EVA® advocates (e.g., Stewart 1991).Bacidore et al. (1997) compared EVA® to "Refined Economic Value Added"(REVA), which applies the cost of capital to the opening market (ratherthan book) value of the firm's equity plus debt. Although both measureswere statistically related to abnormal stock returns, REVA outperformedEVA® in both regression and portfolio tests. Chen and Dodd (1997) ex-amined the explanatory power of accounting measures (earnings pershare, ROA and ROE), residual income, and various EVA®-related mea-sures. They found that EVA® measures outperformed accounting earn-ings in explaining stock returns, but the associations were not as strongas suggested by EVA® proponents (maximum R̂ = 41.5 percent). In ad-dition, accounting earnings provided significant incremental explanatorypower above EVA®, leading the authors to conclude that firms should notfollow EVA® advocates' prescription to replace traditional accounting mea-sures completely with EVA®. Finally, residual income provided nearlyidentical results to EVA®, without the need for the accounting adjust-ments advocated by Stern Stewart.

Biddle et al. (1998) provide the most comprehensive study of EVA®'svalue relevance to date. Their analyses examined the power of accountingmeasures (earnings and operating profits) to explain stock market returnsrelative to EVA® and five components of EVA® (cash fiow from operations,operating accruals, after-tcix interest expense, capital charge, and ac-counting adjustments). They found that traditional accounting measuresgenerally outperformed EVA® in explaining stock prices. While capitalcharges and Stern Stewart's adjustments for accounting "distortions" hadsome incremental explanatory power over traditional accounting mea-sures, the contribution from these variables was not economically signif-icant. Sensitivity analyses indicated that these results were robust toStern Stewart's grouping of firms into five "types" based on their past op-erating returns and growth rates, the time period examined, and the de-pendent variable used in the tests (i.e., stock returns or levels or the timeframe used to compute the market measures).

Managerial Implications of Economic Value MeasuresFrom a managerial accounting standpoint, the key question is not

whether economic value measures are more highly correlated with stockreturns than traditional accounting measures, but whether the use of ec-onomic value measures for internal decision-making, performance mea-surement, and compensation purposes improves organizational perform-ance. Wallace's (1998a) examination of relative performance changes in 40adopters of residual income-based measures such as EVA® and amatched sample of non-users supports claims that these measureschange managerial behavior. Compared to the control firms, the residual


income firms decreased new investments, increased payouts to share-holders through share repurchases, eind utilized assets more intensively,leading to significantly greater change in residual income.^ Wallace(1998a) also found weak evidence that stock market participants re-sponded favorably to the adoption of residual income-based compensationplans.

A related issue is whether the performance implications of economicvalue measures depend upon how the measures are used within the or-ganization. Stern Stewart argues that effective implementation of EVA®requires firms to make this measure the cornerstone of a total financialmanagement system that focuses on EVA® for capital budgeting, goalsetting, investor communication, and compensation (Stern et al. 1995).Stewart (1995) asserts that the poor results from many EVA® implemen-tations are attributable to the fact that EVA® use has not become per-vasive throughout the organization, especially for compensation decisions.A survey by Sibson & Co. supports claims that many users of economicvalue measures do not base compensation on these measures. As shownin table 3, 41.2 percent of respondents used economic value measures forbusiness planning and financial management purposes. However, only16.7 percent used these measures in incentive plans, of which only 26.3percent made economic value the sole performance measure in theseplans. In addition, many of the respondents used economic value mea-sures only in annual incentive plans and not in long-term plans, and rel-atively few used them at all organizational levels.

Biddle et al. (1998) provide some evidence that the use of economicvalue measures in compensation plans is associated with the measures'effectiveness. The only subsample in which EVA® outperformed tradi-tional accounting measures in predicting stock returns was firms usingEVA® in compensation plans. Similarly, the Sibson & Co. survey in table3 indicates that 26.3 percent of firms using economic value measures inincentive plans reported that these measures were "very successful" and36.8 percent reported they were "marginally successful." None of the re-spondents stated that the measures were "not successful." The 31.5 per-cent of respondents who were "not sure" of the measures' effectivenesswere all recent adopters.

Wallace's (1998b) survey of EVA® users found that firms includingEVA® in their incentive compensation plans also implemented the mea-sure to a significantly greater degree for capital budgeting and dividenddecisions, but not for asset disposal, working capital management, sharerepurchase, or financing decisions. Firms using EVA® in incentive plansalso reported significantly greater awareness of the cost of capital, reducedaverage accounts receivable age, increased use of debt, increased salesrevenues and a longer accounts payable cycle. However, changes in the

Wallace (1998a) found no significant difference between users of EVA® and users of otherresidual income-based measures. Wallace's (1998a) tests did not examine whether the re-sidual Income firms achieved higher accounting and stock performance levels than thecontrol sample after adopting the new measures. Although the change in performance forfirms adopting residual Income measures was greater than the control sample, the studydid not examine whether the performance of the residual income firms remained below theaverage performance levels of the control sample after the improvements.


TABLE 3Uses of Economic Value Measures in Business Planning and Incentive

Plans: 1995 Survey of 114 Firms by Sibson & Co.

Economic value used in business planning/financial management* 41.2%Economic value used as a performance measure in incentive plans 16.7If economic value is used in incentive plans:

Used in annual incentive plans only 42.1Used in long-term incentive plans only 10.5Used in annual and long-term incentive plans 47.4Used in corporate and business unit management plans only 52.6Used in corporate management plans only 5.3Used in business unit management plans only 31.6Used in corporate, business unit, and small group plans 10.5Economic value is the sole performance measure in incentive plans 26.3Effectiveness of economic value as a measure in the incentive plan:

Very successful 26.3Moderately successful 36.8Not successful 0.0Not sure 31.5No response 5.3

survey defined economic value as cash flow or earnings above the cost ofcapital or discounted cash fiow, including measures such as economic valueadded, cash fiow return-on-investment, economic profit, or residual profit.

degree of selectivity in the choice of new investment projects, inventoryturnover, share repurchases and debt repayment were not statistically dif-ferent in the two EVA® user groups.

Research TopicsClaims regarding the superiority of economic value measures, as well

as the limited academic research on the topic, suggest a number of ave-nues for future studies. Perhaps the most important question is the long-term performance benefits from the adoption of economic value measures.Consistent with Wallace's (1998a) event study results, some stock marketanalysts are now taking the implementation of internal EVA® systems intoconsideration when recommending companies. BT Alex. Brown, for ex-ample, has put a "strong buy" rating on JC Penney, in part because thefirm is installing an EVA® system {Director's Alert 1998).^ Future researchcan determine whether the market's expectation of higher stock returnsfrom EVA® adopters is accurate.

Second, considerable debate exists on the relative value relevance ofthe alternative economic value measures. Consulting firms battle over thesuperiority of their economic value measures, charging that competitors'measures have fiaws that compromise their predictive ability (Myers 1996;

Although many analysts In the United States and United Kingdom are using EVA® to eval-uate firms. Its use Is not universally embraced. Merrill Lynch, for example, has attackedEVA®, claiming that they have found little evidence that the measure relates to enhancedshareholder value (Director's Alert 1998).


The Economist 1996). However, the relative ability of different economicvalue measures (EVA®, CFROI, or variants of these measures) to predictstock returns is unknown.* If, as might be expected, one measure doesnot consistently exhibit superior predictability, researchers can attemptto determine the factors explaining cross-sectional differences in the pre-dictive ability of alternative economic value measures. Structural and en-vironmental variables such as firm strategy, competitive environment, andproduct or industry life cycle, for example, are likely to be important de-terminants of the relative explanatory power of different economic valuemeasures, as well as the explanatory power of traditional accountingmeasures.

Third, no evidence exists on the factors infiuencing the adoption andperformance consequences of economic value measures for internal pur-poses. Advocates of economic value measures such as EVA® suggest thatthese measures may not be applicable in industries such as financial ser-vices (which are required to set aside capital for regulatory reasons), or invery young companies where revenue calculations frequently are subjectto guesswork [The Economist 1996). Similarly, our discussions with EVA®.adopters indicate that economic value measures can be problematic forfirms in highly cyclical industries, where exogenous factors may causeEVA® to be negative in many periods, even though managers have takenthe appropriate actions.

Stern Stewart argues that effective implementation of EVA® also re-quires their measure to become the cornerstone of a total financial man-agement system (Stern et al. 1995). The firm attributes the lack of successin many EVA® implementations to four factors: (1) EVA® is not made away of life; (2) EVA® is implemented too fast, (3) lack of conviction by theCEO or division head, and (4) inadequate training (Stewart 1995). BraxtonAssociates, in turn, states that a value-based system using CFROI will beunsuccessful without a value driver analysis that unbundles CFROI intodiscrete, controllable financial and operational variables (Snyder 1995).These discussions suggest a number of testable hypotheses regarding de-terminants of the measures' effectiveness.

The internal benefits from economic value measures may also varywith the chosen metric. Critics of CFROI, for example, argue that this mea-sure is too complex for managers to understand and act upon, even if itis conceptually superior to traditional accounting measures and EVA®(Birchard 1994; Myers 1996). EVA® has also been criticized for being toocomplex for front-line managers to use, for motivating managers to reducebeneficial capital expenditures to improve short-term EVA®, and for ig-noring the firm's "core competencies" and providing little actionable in-formation on the long-term drivers of firm value (Birchard 1994; Hamel1997). Research examining (1) key implementation issues infiuencing thesuccess or failure of various economic value measures, and (2) the extent

•* An mternal study by Monsanto using data from competitors, suppliers, customers andother companies in the St. Louis area found that the correlation with stock market per-formance over a 20-year period was substantially higher using CFROI than using EVA®(Myers 1996). However, a comprehensive analysis of this issue using contemporary capitalmarket research methods has not been conducted.


to which the alternative metrics produce distinctly different functional anddysfunctional managerial behavior can shed light on the factors affectingthe effectiveness of economic value measures.

A growing number of firms have tried and abandoned one or more ofthe economic value measures (Birchard 1994; Myers 1996), providing anatural opportunity to study differences between successful and unsuc-cessful adopters of these innovations. For example, AT&T was once toutedin the business press as a leading proponent of EVA® (Tully 1993), buthas since abandoned this measure. Table 4 describes the evolution inAT&T's use of EVA® in its senior management performance measurementsystem. Prior to an internal reorganization in the early 1990s, perform-ance was evaluated based on measured operating income and measuredoperating units (a service volume indicator), and no variable compensationwas awarded. In 1992, the firm adopted EVA® for decision-making andcompensation purposes, and implemented an EVA®-based bonus plancovering approximately 110,000 employees. However, EVA® was supple-mented by two new nonfinancial measures ("customer value added" [CVA]and "people value added" [PVAp) within two years, and was abandonedaltogether by 1997 in favor of traditional accounting measures.

Our interviews with EVA® implementers and users in AT&T and itsoffspring (Lucent Technologies and NCR) identified three primary reasonsfor the measure's demise.

1. The measure was too complex for most employees to understand, eventhough AT&T made relatively few of the accounting adjustments rec-ommended by Stern Stewart. Despite extensive training in the com-putation and use of EVA®, employees outside of corporate headquar-ters did not understand how their actions affected EVA® results, andfelt they had limited ability to impact corporate or business unit EVA®targets. In 1995, NCR was the first AT&T unit to abandon EVA® dueto its perceived complexity, choosing to focus on ROA and contributionmargin. Lucent's new management team also chose not to continueEVA® measurement after the unit's spin-off, feeling that EVA® wassimilar but more complex than traditional accounting measures suchas ROA.

2. The company came to recognize that EVA® was an historical measurethat provided incomplete information on key drivers of future perform-ance, such as employees and customers. In addition, the company'sefforts to win the Malcolm Baldrige National Quality Award requiredcustomer-related measures to become a major component of their per-formance measurement system. As a result, EVA® was supplementedby the CVA and PVA measures, which continue to be included in man-agers' individual performance goals.

3. Although internal EVA® results were positive, total shareholder returnbetween December 1992 and December 1996 (the period covered by

"People value added" (PVA) was based on employee satisfaction, work force diversity, em-ployee turnover / retention, work force health, and leadership visibility. "Customer valueadded" (CVA) was based on customers' satisfaction with price and with product, serviceand contact quality.


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the EVA® measure) was -6.46 percent.^ The inconsistencies betweenreported EVA® and stock returns, combined with the hiring of a newCEO who had not championed the EVA® system, led the firm to dropEVA® in favor of traditional accounting performance measures theybelieve to be more closely aligned with analysts' forecast models andshareholder value.

Although far from definitive, the AT&T example suggests several ex-planations for EVA® implementation results. More detailed comparativestudies using matched samples of successful and unsuccessful imple-mentations can help determine the extent to which these and other ex-planations account for the effectiveness of economic value measures.

NONFINANCIAL PERFORMANCE MEASURESWhile some firms are attempting to overcome perceived limitations in

traditional accounting-based performance measures using economic-value metrics, others are embracing the use of nonfinancial measures fordecisionmaking and performance evaluation. In particular, many firms areimplementing "balanced scorecard" systems that supplement traditionalaccounting measures with nonfinancial measures focused on at leastthree other perspectives —customers, internal business processes, andlearning and growth (Kaplan and Norton 1992, 1996). Proponents of thebalanced scorecard contend that this approach provides a powerful meansfor translating a firm's vision and strategy into a tool that effectively com-municates strategic intent and motivates performance against establishedstrategic goals.

Case studies by Fisher (1995) and Brancato (1995) have identifiedthree principal reasons firms are adopting nonfinancial measures.

1. Perceived Limitations in Traditional Accounting-Based Measures. Com-panies believed that, relative to key nonfinancial indicators, traditionalaccounting measures (1) are too historical and "backward-looking," (2)lack predictive ability to explain future performance, (3) reward short-term or incorrect behavior, (4) are not actionable, providing little in-formation on root causes or solutions to problems, (5) do not capturekey business changes until it is too late, (6) are too aggregated andsummarized to guide managerial action, (7) refiect functions, notcross-functional processes, within a company, and (8) give inadequateconsideration to difficult to quantify "intangible" assets such as intel-lectual capital.'' By incorporating nonfinancial Indicators into theirmeasurement systems, many firms sought to create a wider set ofmeasures that capture not only firm value, but also the factors leadingto the creation of value in the business.

2. Competitive Pressure. Many firms experienced a perceived shock totheir operating environments that motivated meinagement to find newways of managing, measuring and controlling operations. The sub-stantial changes in the nature and intensity of competition forced

^ Over the same period, total shareholder returns were 16.44 percent for MCI and 112.46percent for Sprint, AT&Ts two primary competitors for long-distance telephone services.

^ For additional discussions on nonfinandeil measures of Intangible assets and intellectualcapital, see Edvinsson and Malone (1997) and Stewart (1997).


firms to determine and measure the nonfinancial "value drivers" lead-ing to success in the new competitive environment. The greater em-phasis placed on nonfinancial measures in firms facing competitivepressure is consistent with research finding positive associations be-tween perceived environmental uncertainty and the demand for broad-based information systems incorporating nonfinancial indicators (e.g.,Chenhall and Morris 1986).

3. Outgrowth of Other Initiatives. Other firms adopted nonfinancial mea-sures as an outgrowth of improvement initiatives that required newperformance indicators, especially the adoption of total quality man-agement (TQM) programs. Many management accounting researchersargue that effective TQM requires timely, detailed process informationfor identifjang the sources of defects and monitoring the consequencesof subsequent improvement activities — information that typically isnot available from aggregate accounting data (e.g., Kaplan 1983; John-son 1992). The quality management literature also maintains thatTQM requires greater emphasis on customer requirements and cus-tomers' satisfaction with the firm's products or services, leading togreater emphasis on nonfinancial customer measures such as com-plaints, satisfaction and retention (e.g., U.S. Department of Commerce1997). While some case study sites limited the adoption of nonfinan-cial measures to quality-related issues, others looked upon the needfor new quality measures as an opportunity for a more extensive over-haul of their measurement processes (Brancato 1995).

Current ResearchSeveral related research streams have examined various issues raised

by these case studies. One stream focuses on claims that nonfinancialmeasures are "leading" indicators that provide information on future per-formance that is not contained in current accounting measures. Althoughthe performance measurement literature claims that predictive ability isone of the primary benefits of nonfinancial measures, studies indicate thatfirms experience considerable difficulty linking these measures to futureaccounting or stock price performance. Brancato (1995), for example, re-ported that none of her case study participants could precisely quantifythe link between key nonfinancial performance measures and thebottom line. Our survey of vice presidents of quality for major U.S. firmsfound similar problems relating quality and customer satisfaction mea-sures to accounting and stock returns. As shown in table 5, 75 percent ofthe senior quality executives felt pressure to demonstrate the financialconsequences of their quality initiatives, but fewer than 55 percent coulddirectly relate their quality measures to operational, productivity, or rev-enue improvements, only 29 percent to accounting returns, and just 12percent to stock returns. Similarly, only 28 percent could link customersatisfaction measures to accounting returns and 27 percent to stock re-turns. As a result, 52 percent of the executives found it difficult to identifythe quality improvement opportunities offering the highest economic re-turns, and none found this to be an easy task.

Consistent with the survey evidence, studies investigating the link be-tween nonfinancial measures and future financial performance have pro-duced mixed results. The majority of these studies have examined the


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association between customer satisfaction measures and subsequent ac-counting or stock returns. Banker et al. (1998), for example, found positiveassociations between customer satisfaction measures and future account-ing performance in 18 hotels managed by a hospitality firm, while Ittnerand Larcker (1996) provided evidence that hedge portfolios formed on thebasis of customer satisfaction measures outperformed the stock marketin subsequent periods. Anderson et al. (1994, 1997) supported the hy-pothesis that, on average, customer satisfaction in 77 Swedish firms waspositively related to contemporaneous accounting return on investment,but found weaker or negative relations in service firms. Similarly, Ittnerand Larcker's (1998) investigation of customer, business unit and firm-level data supported claims that customer satisfaction measures are lead-ing indicators of future customer purchase behavior (retention, revenueand revenue growth), growth in customers, changes in business unit ac-counting performance, cind current market values. However, the firm-levelresults varied by industry, with positive relations in some industries andnegative or insignificant relations in others. Foster and Gupta's (1997) in-vestigation of the association between satisfaction measures for individualcustomers of a wholesale beverage distributor and current or future cus-tomer profitability also found positive, negative, or insignificant relationsdepending upon the questions included in the satisfaction measures orthe model specification (levels or percentage changes).

A second research stream has emphasized the use and performanceconsequences of nonfinancial measures in organizations adopting TQM orother advanced manufacturing practices. Nearly all of these studies havefound positive associations between the emphasis placed on TQM, just-in-time (JIT) production practices, or manufacturing fiexibility and theprovision of nonfinancial measures such defect rates, on-time delivery,and machine utilization (e.g., Daniel and Reitsperger 1991a, 1991b;Banker et al. 1993; Abernethy and Lillis 1995; Perera et al. 1997). Positiveassociations have also been found between TQM and the use of nonfinan-cial measures in reward systems (Ittner and Larcker 1995, 1997; Danielet al. 1995). However, empirical support for the hypothesized performancebenefits from these measurement practices is marginal at best. Young andSelto (1993) found little evidence that the provision of nonfinancial oper-ational measures to workers in a JIT facility was associated with differ-ences in manufacturing performance or workgroup performance ratings.Ittner and Larcker (1995) found that information and reward systems thatplaced greater emphasis on nonfinancial Information were associated withhigher ROA in organizations making relatively little use of formal TQMpractices, but not in organizations with extensive TQM programs. Fur-thermore, the performance consequences of quality-oriented performancemeasures varied somewhat across the automotive and computer indus-tries, suggesting that the use of these measures must be adjusted to refiectthe firm's production and competitive environment (Ittner and Larcker1997). Symons and Jacobs' (1995) examination of a TQM-based rewardsystem indicated that the introduction of the system was associated withhigher production output, lower scrap, and reduced product variability,but did not investigate the incentive plan's effect on costs or profitability.Abernethy and Lillis' (1995) study of management control systems in fiex-ible manufacturing plants Implied that greater reliance on nonfinancial


manufacturing measures had a greater positive effect on perceived per-formance in fiexible firms than in nonfiexible firms. However, a similarstudy in plants following a "customer-focused" manufacturing strategyfound no association between the use of nonfinancial measures and per-ceived performance (Perera et al. 1997).

A third research stream has examined the use of nonfinancial mea-sures in compensation plans. Thirty-six percent of firms placing explicitweights on performance measures in their CEO bonus plans in 1993 and1994 included nonfinancial measures (Ittner, Larcker, and Rajan 1997).The mean weight on nonfinancial performance in these plans was 37.1percent of the bonus award, with the average firm including three per-formance measures in the bonus formula (two nonfinancial and one fi-nancial).^ Significant determinants of the weight placed on nonfinancialmeasures included the extent to which the firm followed an innovation-oriented or "prospector" strategy, the adoption of strategic quality initia-tives, the length of product development and product life cycles, regula-tion, and "noise" in traditional financial measures (Bushman et al. 1996;Ittner, Larcker, and Rajan 1997). Although these studies suggest that thedesirability of including nonfinancial measures in compensation contractsis contingent on a variety of factors, little evidence exists on the relationbetween the "match" between incentive plan performance measures andfirm characteristics and the performance benefits arising from the use ofnonfinancial measures. In one of the few studies examining this issue,Govindarajan and Gupta (1985) found that the benefits from nonfinancialcompensation criteria are contingent on a business unit's strategy, withgreater reliance on long-run nonfinancial criteria (sales growth, marketshare, new product and market development, research and development,personal development, and political/public affairs) having a stronger pos-itive impact in units following a "build" strategy than in those following a"harvest" strategy.

Surprisingly little research has been conducted on the implementationor performance consequences of the balanced scorecard concept, despitewidespread practitioner interest in the subject. Table 6 provides descrip-tive statistics from a survey of balanced scorecard implementations by theconsulting firm Towers Perrin. Balanced scorecard adopters continue toplace the majority of weight on financial measures (mean = 56 percent),followed by customer measures (19 percent) and internal process mea-sures (12 percent). Corporate and division-level measures are most com-mon, with relatively little weight placed on subsidiary or other (e.g., de-partment or team) measures. Although Kaplan and Norton (1996) arguethat the proper role of the balanced scorecard in determining compensa-tion is not yet clear, 70 percent of respondents already base compensationon the balanced scorecard or some variant that incorporates financial andnonfinancial measures, and 17 percent are actively considering usingtheir scorecards for this purpose. An additional 15 percent use their score-cards for evaluating performance but not for compensation purposes.

For example, Chrysler's 1994 Incentive contract determined executives' annual bonusesbased 40 percent on vehicle quality Improvements (warranty repairs per 100 vehicles sold),20 percent on customer satisfaction, 20 percent on market share and 20 percent on finan-cial performance (pre-tcix earnings).


TABLESBalaneed Scorecard Implementations in 60 FirmsResponding to a 1996 Survey by Towers Perrin

Relative weight placed on the foUowing perspectives (mean response):Financial 56%Customer 19Internal business 12Innovation and learning 5Other 9

Types of performance measures under the balanced scorecard approach(check all that apply):Corporate 57Division/group 65Subsidiary 22Other (e.g., department, team, etc.) 22

Uses of the balanced scorecard approach in compensation:Used in incentive compensation awards 37Used for evaluating performance, but not for determining 15

incentive compensation awardsNot used for Incentive compensation, but use a variation that 33

considers both flnancial and operational measuresThe same scorecard is used for everyone in the plan 23Top executives are Included In the balanced scorecard plan 37

Problems experienced implementing the balanced scorecard (n = 57):

Not a MajorProblem Problem

1 2 3 4 S

Difficult to evaluate relative importance ofmeasures 2% 25% 35% 29% 9%

Time and expense involved 7 25 43 20 5Requires quantification of quaiitatlve data 7 18 30 36 9Large number of measures dilute overall

impact 9 23 25 36 7Dlfflcult to decompose goals for lower levels

in organization 12 18 36 25 9Requires a highly-developed Information

system 13 18 25 35 9

Effectiveness of the balanced scorecard compared to performancemeasurement approaches used in the past:

Employee understanding ofperformance measuresand goals (n = 40)

Satisfaction or value received(n = 39)

SignificantlyLower

1

0%

0

2

18%

5

AsEffective

3

45%

31

4

32%

54

SignificantlyHigher

5

5%

10


Scorecards generally are modified for individual managers, with top ex-ecutives included in 37 percent of the scorecard incentive plans.

Kaplan and Norton (1996) contend that the balanced scorecard pro-vides a number of mechanisms for linking long-term strategic objectiveswith short-term actions. According to these authors, development of thebalanced scorecard forces managers to develop a consensus around thefirm's vision and strategy, and allows managers to communicate the firm'sstrategy throughout the organization. This communication ensures thatemployees understand the long-term strategy, the relations among thevarious strategic objectives, and the association between the employees'actions and the chosen strategic goals. The balanced scorecard is alsoexpected to help firms allocate resources and set priorities based on theinitiatives' contribution to long-term strategic objectives, and to providestrategic feedback and promote learning through the monitoring of short-term strategic results.

Empirical support for these claims is limited. Although 64 percent ofthe Towers Perrin respondents reported that the satisfaction or value re-ceived from their balanced scorecard systems was higher or significantlyhigher than that received from other performance measurement ap-proaches, only 37 percent felt that employees' understanding of perform-ance measures and goals was higher under the scorecard than underother approaches and 18 percent thought it was lower. Similarly, Ittner,Larcker, and Meyer's (1997) study of a balanced scorecard compensationsystem in retail branch banks found no evidence that the scorecard ap-proach enhanced branch managers' understanding of business goals,plans for meeting these goals, or connections between the managers' joband business objectives. Moreover, the perceived adequacy of informationabout progress against the multiple business goals was statistically lower.

Research TopicsThe primary research question arising from the use of nonfinancial

measures and the balanced scorecard is the net economic benefits fromthese measurement practices. Despite increasing use of nonfinancial mea-sures, many firms believe that performance measures should be purelyfinancial in order to focus efforts on the ultimate goals of the firm (Newman1991; Kurtzman 1997). Similarly, some EVA® advocates claim that a bal-anced scorecard of financial and nonfinancial measures hinders perform-ance because there is no single overall measure of performance on whichmanagers can concentrate their efforts to improve [Journal qf Applied Cor-porate Finance 1997, 65). The implementation of more complex measure-ment systems can also be quite costly. As shown In table 6, 25 percent ofthe respondents to the Towers Perrin survey experienced problems or ma-jor problems with the extra time and expense required to implement andoperate the balanced scorecard, and 44 percent encountered problemsdeveloping the extensive information systems needed to support the score-card approach. Combined with the weak performance results in priorstudies of nonfinancial performance measures, these Issues raise impor-tant questions about the net benefits from incorporating nonfinancial met-rics into performance measurement systems.

If nonfinancial performance measures are not beneficial in all settings,an important research topic is identifying the circumstances under which


these systems do improve performance. As highlighted in our literaturereview, prior studies suggest that the link between nonfinancial measuressuch as customer satisfaction and subsequent accounting and stock mar-ket performance vary across industries. Similarly, the use and perform-ance consequences of these measures appear to be affected by organiza-tional strategies and the structural and environmental factors confrontingthe organization. Future research can make a significant contribution byproviding evidence on the contingency variables affecting the predictiveability, adoption and performance consequences of various nonfinancialmeasures and balanced scorecards.

Another key issue is defining precisely what "balance" is and themechanisms through which "balance" promotes performance. A commonview, perpetuated by early writings on the balanced scorecard concept(e.g., Kaplan and Norton 1992), is that "balance" is achieved by diversemeasurement in the domains of financial performance, operational per-formance, performance for the customer, and learning and innovation.According to this view, multiple measures in each of several domains min-imize the risk that information germane to business results will be lost.More recently, Kaplan and Norton (1996) argue that a balanced scorecardis not merely a collection of financial and nonfinancial measures in variouscategories, but an integrated set of measures developed from a "theory ofthe business" that explicitly links the scorecard metrics in a causal chainof performance drivers and outcomes. This view, originally outlined byEccles (1991), contends that a firm's "business model" must be under-stood before a "balanced" scorecard of performance measures can be cho-sen and implemented.

Figure 1 illustrates the business model developed by Sears Roebuckand Company (Rucci et al. 1998). The basic model consists of employee,customer and shareholder components. After considerable data collectionand statistical refinement. Sears identified several key value drivers (e.g.,increases in employee attitude have a direct impact on customer impres-sion, and customer impression has a direct impact on the future account-ing performance of individual stores). Sears claims that customer satis-faction increased 4 percent after incorporating the results from this modelinto the choice of quality/customer initiatives and the design of their long-term performance plan.^ The increase in customer satisfaction led to anestimated $200 million increase in revenues, and ultimately an estimated$250 million increase in market capitalization (based on their currentafter-tax margins and price-earnings ratio).

The business model approach to the selection of performance mea-sures raises a number of potential research questions. Although estab-lishing the firm's business model prior to selecting measures has the ad-vantage of sharpening strategic focus and organizational priorities, it can

One Interesting question is whether statistical relations between the measures and desiredoutcomes (e.g., stock price or accounting performance) should be used when designingperformance evaluation and compensation plans. Analytical research by GJesdal (1981),Paul (1992) and Feltham and Xle (1994) shows that an information system that is usefulfor valuing the firm need not be useful in assessing a manager's performance. Conse-quently, just because one economic value measure or nonfinancial Indicator predicts stockreturns or accounting performance better than an alternative measure does not necessarilyimply that the same measures or weights should be used to evaluate and reward managers.


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be difficult to establish the reliability and predictive validity of the multiplemeasures in the business model without having done a great deal of mea-surement and analysis in the first place.'" Moreover, there is no guaranteethat a business model based on current measures and competitive envi-ronments will be relevant to the choice of performance measures if thereare major shifts in the firm's environment. Future research can provideguidance as to which conception of "balance"—variety in measurement orselection of a smaller set of measures based on their current reliabilityand predictive validity (which may not hold in the future)—best promotesdesired business outcomes.

It would also be instructive to study the development and use of busi-ness models in a diverse set of organizations to determine whether theclaimed success at Sears can be replicated in other settings, and to in-vestigate how business models vary across organizational life cycles, com-petitive environments, corporate strategies, and other contextual factors.Nagar's (1998) study of retail banks, for example, found that the nonfi-nancial drivers of future accounting performance vary significantly withthe bank's competitive strategy. It may also be possible to develop moregeneral business models for estimating the economic impact of quality,customer, or other improvement initiatives. For example, research bySterman et al. (1997) on the performance consequences of TQM at AnalogDevices is a novel attempt to use a detailed business model to understandcomplex interrelations among a broad set of financial and nonfinancialmeasures. Although this research requires extensive data collection anddetailed institutional knowledge, the resulting insights can challengeexisting assumptions regarding the relations between performancemeasures.

The use of multiple financial and nonfinancial measures also leads toquestions on the value of including a broad set of metrics in performancemeasurement systems. Studies on "information overload" suggest that alarge number of measures can reduce performance by exceeding manag-ers' processing capabilities when making judgements. ̂ ^ A diverse set ofperformance measures may also cause managers to spread their effortsover too many objectives, reducing the effectiveness of the performancemeasurement system. More than 40 percent of the Towers Perrin respon-dents stated that the large number of measures in the balanced scorecarddiluted the overall impact of the new measurement systems. Similarly, astudy by the Consortium for Alternative Reward Strategies Research foundthat the performance benefits from reward plans for nonmanagement em-ployees peaked when the plans used 3-5 performance measures and de-clined thereafter (McAdams and Hawk 1994). Holmstrom and Milgrom's

'" Reliability refers to the extent of noise or measurement error in a measure, and validity tothe extent to which the measure does what it is intended to do. Predictive validity is oneof the key attributes of interest when selecting performance measures. From an accountingstandpoint, a crucial test is whether a broad set of nonfinancial measures such as em-ployee satisfaction, employee turnover, product development cycle time, and supplier re-lations possess incremental ability to predict future financial performance, after controllingfor the predictability of past financial performance.

" See Schlck et al. (1990) for a review of accounting studies on information overload. Incontrast to the Information overload hypothesis, an experiment by Lipe and Salterio (1998)found that performance evaluations were not affected by increasing the number of mea-sures when these measures were organized into the four balanced scorecard categories.


(1991) analytical model adds that multi-criteria incentive contracts maydirect agents' effort to tasks that are easily measured at the expense oftasks that are harder to measure, even if this allocation of effort is detri-mental to the firm. Their model indicates that the advantages of addingnew performance measures to an incentive contract decrease with the dif-ficulty of measuring performance in any other activities that make com-peting demands on the agent's time and attention. Thus, the net benefitfrom including a larger number of metrics in performance measurementsystems is unclear.

It is also unclear whether decisions using multi-criteria performancemeasurement systems should be computed using explicit, objective for-mulae that prescribe the weights to be attached to each measure, orshould be based on subjective evaluations where the weight attached toeach measure is implicitly or explicitly chosen by the decision maker. Forexample, many firms rank quality improvement opportunities using somequality measures denominated in financial terms (e.g., scrap dollars orwarranty expenses), some in percentages or counts (e.g., defect rates orcustomer complaints), and some in arbitrary survey scale points (e.g., cus-tomer satisfaction indices).'^ As a result, managers must combine thevarious measures using pre-determined formulae or subjective weightingof the various measures' importance when selecting improvement pro-jects. ̂ ^ Similarly, performance evaluation and compensation decisions inmulti-criteria systems can be based on formulaic or subjective weightingsof the various measures. Kaplan and Norton (1996) highlight three poten-tial difficulties in integrating the balanced scorecard measures intoformula-based compensation plans. First, the firm must determine theappropriate weights to place on the multiple performance measures. TheTowers Perrin survey suggests this is a difficult task in many organiza-tions, with 38 percent of the respondents experiencing problems in eval-uating the relative importance of the scorecard measures. Second, for-mulaic compensation plans may be susceptible to the game-plajringassociated with explicit, formula-based rules. Finally, formula-basedplans may allow bonuses to be paid even when performance is "unbal-anced" (i.e., over-achievement on some objectives but under-achievementon others).**

Some firms using multiple financial and nonfinancial performancemeasures for performance evaluations have abandoned formula-based

'̂ See Hemmer (1996) for a model providing insight into the conditions under which differenttjTses of nonflnancial measures (e.g., levels vs. ratios) are appropriate.

'̂ For example, Xerox rates quality improvement projects using subjective assessments offour factors: (1) cost of poor quality reduction, (2) external customer impact, (3) ability tocontrol the solution, and (4) degree of difficulty in resolving the problem. Each factor israted on a scale ranging from 1 = little to 5 = great, and the average of the four subjectiveassessments is used to rank improvement alternatives.

'•* Strategy researchers point out that the use of formal, pre-set goals and milestones instrategic control systems such as the balanced scorecard may also prevent the adaptabilityand flexibility that is the essence of good strategy (e.g., Quinn 1980; Mintzberg 1987). Inaddition, case studies by Lorange and Murphy (1984) and Goold and Quinn (1993) indicatethat formal strategic control systems may reduce performance by focusing attention onincomplete or incorrect goals and performance measures, and fostering behavioral andpolitical barriers that adversely affect the utility of the strategic controls.


plans in favor of subjective appraisals in order to minimize these difficul-ties. Indeed, Kaplan and Norton (1996, 220) argue that the balanced score-card renders subjective compensation systems "easier and more defensi-ble to administer..;and also less susceptible to game playing." Analyticalstudies indicate that subjective compensation plans Ccin be superior toobjective, formula-based plans because they allow the firm to exploit non-contractable information that might otherwise be ignored in formula-based contracts. For example, Baiman and Rajan (1995) show that dis-cretionary bonus schemes, in which an objectively-determined bonus poolis allocated to managers based on subjective evaluations of the managers'performance, enable the owner to use noncontractible information suchas nonquantifiable or "soft" measures (e.g., the principal's personal ob-servations of the manager's ability or effort level) to achieve an optimalimprovement in managerial effort. Similarly, Baker et al.'s (1994) theoret-ical analysis indicates that the use of subjective weights on objective per-formance measures allows the employer to mitigate distortions in perform-ance measures by "backing out" unintended dysfunctional behavior orgaming induced by the incomplete objective performance measures.

Despite these advantages, subjective performance evaluations have anumber of potential drawbacks. Prendegast and Topel's (1993) review ar-ticle identifies several reasons why subjective performance evaluationsmay be inferior to objective, formula-based evaluations. These includegreater possibility of reneging on promises to reward superior performancesince the subjective measures are not verifiable, increased favoritism andbias in performance evaluations, the tendency to compress subjectiveevaluations and rewards (to avoid giving poor ratings), and greater per-ceived "unfairness" in performance evaluations. Should these possibilitiesmaterialize, workers will exert less effort under a subjective compensationsystem than under a more objective incentive plan.'^ Since the net benefitsof formulaic vs. subjective performance evaluations are unclear, this issueoffers an exciting topic for future research.

Another important question is whether the same measures or score-card used to develop strategic priorities and monitor strategic actionsshould be used to evaluate managerial performance. Although a largenumber of scorecard measures may be desirable for decision-making andperformance monitoring purposes, a smaller number of selected perform-ance measures may be more appropriate for managerial performance eval-uation and compensation purposes. The balanced scorecard literaturealso suggests that performance measures should be tailored for each busi-ness unit. Thus, corporate-level measures may not be applicable to lower-level employees. More than a third of the respondents to the Towers Perrinsurvey, for example, found it difficult to decompose scorecard goals forlower-levels in the organization. Experiments by Schiff and Hoffmann(1996) provide some evidence that firms use different measures for as-sessing organizational and managerial performance. When presented with

In addition, studies have found relatively low correlations between objective and subjectiveperformance ratings, raising questions about which ratings are more accurate or appro-priate. See Bommer et al. (1995) for a review.


a scorecard of financial measures and generally "softer" nonfinancial mea-sures, participants tended to place greater emphasis on the financial mea-sures for evaluating the performance of the business unit and on non-financial measures for evaluating managerial performance. Lipe andSalterio's (1998) experiments, on the other hand, found that when score-cards for two divisions contained some common and some unique mea-sures, performance evaluations were affected only by the common mea-sures. Thus, a potential avenue for research is examining the relativevalue of different types of scorecards and performance measures for dif-ferent purposes.

A final topic is the issue of trade-offs among multiple financial andnonfinancial performance measures. Although "balance" may require amanager to perform well on multiple dimensions, actions taken to improveone measure may lead to short-term declines in other performance mea-sures. A key question is how to retain "balance" in managerial actions andperformance evaluations in the presence of trade-offs. Kaplan and Norton(1996) suggest the use of hurdles to ensure that managers do not receivebonuses when they over-perform on some dimensions but under-performon others. However, a potential problem with hurdles is that they mayfocus undue attention on dimensions requiring minimum performancelevels and may prompt managers to avoid investments that reduce short-term performance on the hurdle dimensions, even if these investmentsare beneficial in the long-term. Additional research is needed on the treat-ment of the inevitable trade-offs that managers will need to make amongvarious financial and nonfinancial performance measures.

PERFORMANCE MEASURMENT INITIATIVES INGOVERNMENT

While most academic discussions of performance measurement issuesfocus on the private sector, recent efforts to "reinvent" the governmenthave emphasized the important role performance measurement systemscan play in improving the efficiency and effectiveness of government op-erations. The Governmental Accounting Standards Board (GASB), for ex-ample, has promoted the reporting of "Service Efforts and Accomplish-ments" (SEA) by state and local governments. The objective of SEAreporting is to provide more complete Information about a governmententity's performance than can be provided by traditional financial state-ments. According to GASB's Concept Statement No. 2, SEA informationshould focus on results-oriented measures of service accomplishments(outputs and outcomes) and measures of the relationships between serviceefforts and service accomplishments (i.e., efficiency), thereby assistingusers in assessing the economy, efficiency and effectiveness of services.

At the federal level, the Government Performance and Results Act(GPRA) seeks to hold federal agencies accountable for program results byrequiring agencies to clarify their missions, set program goals, and mea-sure performance towards those goals. Beglrming in 1999, agencies must(1) establish goals that define the level of performance to be achieved bya program activity; (2) express goals in an objective, quantifiable andmeasurable form; (3) describe the operational processes and resources re-quired to achieve goals; (4) establish performance indicators to be used in


measuring or assessing the relevant outputs, service levels and outcomesof each activity; (5) provide a basis for comparing actual program resultswith established goals; and (6) describe the means for verifying and vali-dating measured values (General Accounting Office 1998). Annual report-ing of program performance begins the following year.

The extent to which government organizations have adopted these per-formance measures varies widely. Table 7 reports descriptive statisticsfrom a survey of 900 state and local government entities conducted by theGovernmental Accounting Standards Board and the National Academy ofPublic Administration (1997). The survey examined the measurement anduse of performance measures related to service efforts and accomplish-ments. Slightly more than half (53.2 percent) of the respondents have

TABLE 7Use and Reporting of Performance Measures inState and Local Government Entities (n = 900)'

Percentage of entities that have developed:

Performance measures 53.2Output or outcome performance

measures 39.3

Percentage of entities that say they use:

Performance measuresOutput or outcome performance

measures

Percentage of entities that use measures for:

Strategic planningResource ailocatlonProgram management and monitoring

Percentage of entities that report measures to:

Internal managementElected officialsCitizens and media

'ercentage of entities that plan to usemeasures for:

Strategic planningResource allocationProgram management and monitoringReporting

46.8

32.9

OutputMeasures

24.727.726.2

OutputMeasures

25.024.021.2

le to use)

46.358.962.941.9

OutcomeMeasures

23.925.228.0

OutcomeMeasures

24.824.321.0

performance

Source: Adapted from Governmentai Accounting Standards Board and NationalAcademy of Public Administration (1997).

''Entities refer to municipalities, counties, school districts, coileges and universi-ties, pubiic authorities, state departments, pubilc employee retirement systems,and special districts.


developed these performance measures, with 46.8 percent using the mea-sures internally. However, many of these measures are not output- oroutcome-oriented. Only 39.3 percent have developed output or outcomemeasures, and just 32.9 percent use them for decision-making or per-formance evaluation. Less than 29 percent of the entities use output oroutcome measures for strategic planning, resource allocation, or programplanning and monitoring, and 25 percent or fewer use them for internalor external reporting. Although these percentages are relatively low, theuse of performance measures for these purposes is expected to increasedramatically in the future, with 62.9 percent planning to use performancemeasures for program evaluation, 58.9 percent for resource allocation,46.3 percent for strategic planning, and 41.9 percent for reporting.

Financial World's assessments of municipal performance measure-ment and evaluation practices provide additional evidence on the use ofresults-oriented performance measures in local government. Since 1991,Financial World has issued report cards on the financial managementpractices of the 30 largest U.S. cities. Performance measurement systemsare graded based on a number of factors, including the availability of clear,measurable goals, the extent to which performance measures relate tooutcome rather than output measures, the measures' impact on decisions,the testing and benchmarking of performance measurement information,and the use of customer surveys. In 1991, the mean grade was C-I-, withtwo cities receiving As and one (Philadelphia) receiving an F (Barrett andGreene 1992). By 1995 (the latest year covered by the assessment), themean grade improved slightly to B - , and no city received an F (Barrettand Greene 1995). More importantly, several cities made substantial im-provements, with Philadelphia moving from F to C-I-, Memphis from D-l-to B- , and Dallas from B to A-. In contrast, Seattle's grade fell from A-to C-I-. Like the GASB survey results, the Financial World report cardssuggest that state and local governments may provide a unique setting forexamining major differences in performance measurement systems, aswell as the behavioral and performance changes associated with dramaticchanges in measurement practices.

The development and use of results-oriented performance measureshave also increased in the federal government, but remain relatively lim-ited. Despite the approaching deadline for the implementation of results-oriented measurement systems, the General Accounting Office (GAO) sur-vey results in table 8 indicate that 38 percent or fewer federal managershad the tj^es of measures required by the GPRA to a "great" or "very great"extent in 1997. Moreover, only 21 percent used the measures for devel-oping budgets, 20 percent for funding decisions, 13 percent as the basisfor legislative changes, and 16 percent as the basis for program changes.Although these percentages are significantly greater than three years prior(p < 0.10, two-tail), they are far lower than the GAO expected (GeneralAccounting Office 1998). In addition, relatively few of the managers be-lieved that their agencies' efforts to implement the GPRA have had mucheffect on their programs, operations, or projects, and more than halfthought that the GPRA's impact in the future will be modest.

Research TopicsOne research topic prompted by the wide variations in governmental

measurement practices is identification of factors infiuencing the adoption

3 Tears Ago

191119

2717

Currently

32**32**31**

38**26**


TABLE 8Performance Measurement Practices in the U.S. Government

1997 General Accounting Office Survey of Government Managers

Percent of federal managers having these types of measures to a great orvery great extent:Measures that:

demonstrate to someone outside their agencieswhether they are achieving their Intendedresults

tell whether they are satisfying their customersteil about the quality of their product or servicestell how many things they produce or services

they providetell If they are operating efficiently

Percent of federal managers using results-oriented performance measuresfor these purposes to a great or very great extent:Performance measures are:

used to develop tbe agency's budgetused as the basis for funding decisionsused as the basis for legislative changesused as the basis for program changes

Percent of federal managers believing that their agency's efforts to imple-ment the Government Performance and Results Act have improved its pro-grams, operations, or projects to date (of those expressing an opinion):

To a very great extent 1.2To a great extent 9.1To a moderate extent 31.5To a small extent 36.3To no extent 21.9

Percent of federal managers believing that their agency's efforts toimplement the Government Performance and Results Act will improve itsprograms, operations, or projects iu the future (of those expressing anopinion):

To a very great extent 1.6To a great extent 25.3To a moderate extent 34.1To a small extent 14.4To no extent 5.6

3 Years16149

12

Ago Currently21**20**13*16**

**, * statistically different from three years prior at the 5 percent and 10 percentleveis (two-taii), respectively.

of results-oriented performance measures. For example, nearly half of theGASB survey respondents with performance measures were not legallyrequired to implement the measures. The survey also suggests that theadoption of performance measures varies across different types of govern-ment organizations (e.g., municipalities, counties, state departments,school districts, etc.). An interesting question is why some entities imple-mented these systems while others did not. Similarly, what factors have


motivated some of the cities in the Financial World assessment to makesubstantial improvements their performance evaluation systems? Someindication of the relevant factors may already be available from researchon government accounting practices. Studies of financial accounting anddisclosure in government agencies, for example, suggest that variablessuch as legislative power, the power of the governor or mayor, interest-group strength, political competition, financing requirements, and socio-economic development and diversity are associated with financial report-ing practices (e.g., Evans and Patton 1983; Ingram 1984; Cheng 1992).Management accounting studies, in turn, suggest that the adoption anduse of cost accounting systems in government agencies is related to theextent of internal and external competition and legislative requirements tobe self-funding (e.g., Geiger and Ittner 1996). Performance measurementresearch can build on these studies to identify the determinants of gov-ernmental performance measurement practices.

A second research question is whether the new performance mea-surement systems will actually improve governmental performance. Thereis a long history of unsuccessful management control initiatives in theU.S. government, ranging from management-by-objectives to zero-basedbudgeting. One avenue for research is examining how (or if) the imple-mentation of the new performance measurement systems differs from ear-lier efforts, and how these differences affect performance outcomes. An-other avenue is investigating how other management practices infiuencethe new measures' use and performance benefits. The U.S. ComptrollerGeneral, for example, testified before Congress that greater flexibility andincentives for managers to act creatively are critical to the achievement offundamental improvements in agency performance (U.S. Senate 1993).This claim suggests that efforts to improve government efficiency and ef-fectiveness through improved performance measurement will be unsuc-cessful without complementary changes in other organizational practices.

Perhaps the most fundamental question is whether private sector no-tions of performance measurement and accountability are applicable inthe public sector. Many recent performance measurement initiatives arebased on the idea that legal requirements to measure and report perform-ance indicators will improve governmental performance by increasing theaccountability of government managers. However, institutional theoriesargue that in organizations such as government agencies, whose survivaldepends primarily on the support of external constituents and only sec-ondarily on actual performance, managers will implement the mandatedsystems in order to appear modern, rational and efficient, but will notactually use the systems for Improving performance (e.g., Scott 1987;Gupta et al. 1994). The large-scale implementation of the GPRA's require-ments provides an ideal setting for examining whether mandated perform-ance measurement systems are actually used for internal decision makingand performance evaluation or are simply implemented to legitimate theagencies with Congress and other stakeholders.

CONCLUSIONSThe objective of this paper is to foster research on recent innovations

in performance measurement by providing a rich description of emergingperformance measurement practices and identifying fruitful avenues for


future research. Rather than providing a comprehensive review of per-formance measurement papers, we discuss a targeted selection of relatedpapers that provide a broad overview of potential research opportunitiesrelated to economic value measures, nonfinancial performance measuresand the balanced scorecard, and performance measurement initiatives ingovernment agencies. Although the paper is limited to these three topics,many of the research questions are equally relevant to other importantperformance measurement issues. Including the measurement of inter-organizational relations with suppliers and customers, the evaluation ofjoint ventures, and the choice of performance measures in "global"organizations.

A final issue is the role of consultants in the adoption of new mea-surement practices. It would be useful to know whether economic valuemeasures or the balanced scorecard represent solutions to real problemsfacing firms or are simply fads that consultants have packaged into "prod-ucts" that can be easily sold to corporate management. The ultimate ques-tion is whether there is anything intrinsically superior about these mea-surement practices that produces desirable changes in managerialbehavior. Perhaps the same (or better) results could be obtained with otherperformance metrics, as long as the performance measurement choice ischampioned by senior-level managers. In fact, it is possible that any per-formance consequences are simply due to a "Hawthorne Effect," with thespecific measures having minimal importance. Additional insight into therole of consultants in the adoption of new measurement practices wouldcontribute to our understanding of trends in performance measurement.

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